{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 数据全显示\n",
    "pd.set_option('display.max_columns', None)\n",
    "# 颜色\n",
    "colors = sns.color_palette()\n",
    "# 数据精度\n",
    "pd.set_option('precision', 3)\n",
    "#  解决中文/小数点显示问题\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "plt.rcParams['axes.unicode_minus'] = False"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "项目名称：IBM员工离职数据分析\n",
    "\n",
    "数据来源：https://tianchi.aliyun.com/dataset/dataDetail?dataId=77180"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_path = './data/WA_Fn-UseC_-HR-Employee-Attrition.csv'\n",
    "df = pd.read_csv(data_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1470 entries, 0 to 1469\n",
      "Data columns (total 35 columns):\n",
      "Age                         1470 non-null int64\n",
      "Attrition                   1470 non-null object\n",
      "BusinessTravel              1470 non-null object\n",
      "DailyRate                   1470 non-null int64\n",
      "Department                  1470 non-null object\n",
      "DistanceFromHome            1470 non-null int64\n",
      "Education                   1470 non-null int64\n",
      "EducationField              1470 non-null object\n",
      "EmployeeCount               1470 non-null int64\n",
      "EmployeeNumber              1470 non-null int64\n",
      "EnvironmentSatisfaction     1470 non-null int64\n",
      "Gender                      1470 non-null object\n",
      "HourlyRate                  1470 non-null int64\n",
      "JobInvolvement              1470 non-null int64\n",
      "JobLevel                    1470 non-null int64\n",
      "JobRole                     1470 non-null object\n",
      "JobSatisfaction             1470 non-null int64\n",
      "MaritalStatus               1470 non-null object\n",
      "MonthlyIncome               1470 non-null int64\n",
      "MonthlyRate                 1470 non-null int64\n",
      "NumCompaniesWorked          1470 non-null int64\n",
      "Over18                      1470 non-null object\n",
      "OverTime                    1470 non-null object\n",
      "PercentSalaryHike           1470 non-null int64\n",
      "PerformanceRating           1470 non-null int64\n",
      "RelationshipSatisfaction    1470 non-null int64\n",
      "StandardHours               1470 non-null int64\n",
      "StockOptionLevel            1470 non-null int64\n",
      "TotalWorkingYears           1470 non-null int64\n",
      "TrainingTimesLastYear       1470 non-null int64\n",
      "WorkLifeBalance             1470 non-null int64\n",
      "YearsAtCompany              1470 non-null int64\n",
      "YearsInCurrentRole          1470 non-null int64\n",
      "YearsSinceLastPromotion     1470 non-null int64\n",
      "YearsWithCurrManager        1470 non-null int64\n",
      "dtypes: int64(26), object(9)\n",
      "memory usage: 402.1+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Age</th>\n",
       "      <th>DailyRate</th>\n",
       "      <th>DistanceFromHome</th>\n",
       "      <th>Education</th>\n",
       "      <th>EmployeeCount</th>\n",
       "      <th>EmployeeNumber</th>\n",
       "      <th>EnvironmentSatisfaction</th>\n",
       "      <th>HourlyRate</th>\n",
       "      <th>JobInvolvement</th>\n",
       "      <th>JobLevel</th>\n",
       "      <th>JobSatisfaction</th>\n",
       "      <th>MonthlyIncome</th>\n",
       "      <th>MonthlyRate</th>\n",
       "      <th>NumCompaniesWorked</th>\n",
       "      <th>PercentSalaryHike</th>\n",
       "      <th>PerformanceRating</th>\n",
       "      <th>RelationshipSatisfaction</th>\n",
       "      <th>StandardHours</th>\n",
       "      <th>StockOptionLevel</th>\n",
       "      <th>TotalWorkingYears</th>\n",
       "      <th>TrainingTimesLastYear</th>\n",
       "      <th>WorkLifeBalance</th>\n",
       "      <th>YearsAtCompany</th>\n",
       "      <th>YearsInCurrentRole</th>\n",
       "      <th>YearsSinceLastPromotion</th>\n",
       "      <th>YearsWithCurrManager</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1470.000</td>\n",
       "      <td>1470.000</td>\n",
       "      <td>1470.000</td>\n",
       "      <td>1470.000</td>\n",
       "      <td>1470.0</td>\n",
       "      <td>1470.000</td>\n",
       "      <td>1470.000</td>\n",
       "      <td>1470.000</td>\n",
       "      <td>1470.000</td>\n",
       "      <td>1470.000</td>\n",
       "      <td>1470.000</td>\n",
       "      <td>1470.000</td>\n",
       "      <td>1470.000</td>\n",
       "      <td>1470.000</td>\n",
       "      <td>1470.00</td>\n",
       "      <td>1470.000</td>\n",
       "      <td>1470.000</td>\n",
       "      <td>1470.0</td>\n",
       "      <td>1470.000</td>\n",
       "      <td>1470.000</td>\n",
       "      <td>1470.000</td>\n",
       "      <td>1470.000</td>\n",
       "      <td>1470.000</td>\n",
       "      <td>1470.000</td>\n",
       "      <td>1470.000</td>\n",
       "      <td>1470.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>36.924</td>\n",
       "      <td>802.486</td>\n",
       "      <td>9.193</td>\n",
       "      <td>2.913</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1024.865</td>\n",
       "      <td>2.722</td>\n",
       "      <td>65.891</td>\n",
       "      <td>2.730</td>\n",
       "      <td>2.064</td>\n",
       "      <td>2.729</td>\n",
       "      <td>6502.931</td>\n",
       "      <td>14313.103</td>\n",
       "      <td>2.693</td>\n",
       "      <td>15.21</td>\n",
       "      <td>3.154</td>\n",
       "      <td>2.712</td>\n",
       "      <td>80.0</td>\n",
       "      <td>0.794</td>\n",
       "      <td>11.280</td>\n",
       "      <td>2.799</td>\n",
       "      <td>2.761</td>\n",
       "      <td>7.008</td>\n",
       "      <td>4.229</td>\n",
       "      <td>2.188</td>\n",
       "      <td>4.123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>9.135</td>\n",
       "      <td>403.509</td>\n",
       "      <td>8.107</td>\n",
       "      <td>1.024</td>\n",
       "      <td>0.0</td>\n",
       "      <td>602.024</td>\n",
       "      <td>1.093</td>\n",
       "      <td>20.329</td>\n",
       "      <td>0.712</td>\n",
       "      <td>1.107</td>\n",
       "      <td>1.103</td>\n",
       "      <td>4707.957</td>\n",
       "      <td>7117.786</td>\n",
       "      <td>2.498</td>\n",
       "      <td>3.66</td>\n",
       "      <td>0.361</td>\n",
       "      <td>1.081</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.852</td>\n",
       "      <td>7.781</td>\n",
       "      <td>1.289</td>\n",
       "      <td>0.706</td>\n",
       "      <td>6.127</td>\n",
       "      <td>3.623</td>\n",
       "      <td>3.222</td>\n",
       "      <td>3.568</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>18.000</td>\n",
       "      <td>102.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>30.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1009.000</td>\n",
       "      <td>2094.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>11.00</td>\n",
       "      <td>3.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>80.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>30.000</td>\n",
       "      <td>465.000</td>\n",
       "      <td>2.000</td>\n",
       "      <td>2.000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>491.250</td>\n",
       "      <td>2.000</td>\n",
       "      <td>48.000</td>\n",
       "      <td>2.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>2.000</td>\n",
       "      <td>2911.000</td>\n",
       "      <td>8047.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>12.00</td>\n",
       "      <td>3.000</td>\n",
       "      <td>2.000</td>\n",
       "      <td>80.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>6.000</td>\n",
       "      <td>2.000</td>\n",
       "      <td>2.000</td>\n",
       "      <td>3.000</td>\n",
       "      <td>2.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>2.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>36.000</td>\n",
       "      <td>802.000</td>\n",
       "      <td>7.000</td>\n",
       "      <td>3.000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1020.500</td>\n",
       "      <td>3.000</td>\n",
       "      <td>66.000</td>\n",
       "      <td>3.000</td>\n",
       "      <td>2.000</td>\n",
       "      <td>3.000</td>\n",
       "      <td>4919.000</td>\n",
       "      <td>14235.500</td>\n",
       "      <td>2.000</td>\n",
       "      <td>14.00</td>\n",
       "      <td>3.000</td>\n",
       "      <td>3.000</td>\n",
       "      <td>80.0</td>\n",
       "      <td>1.000</td>\n",
       "      <td>10.000</td>\n",
       "      <td>3.000</td>\n",
       "      <td>3.000</td>\n",
       "      <td>5.000</td>\n",
       "      <td>3.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>3.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>43.000</td>\n",
       "      <td>1157.000</td>\n",
       "      <td>14.000</td>\n",
       "      <td>4.000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1555.750</td>\n",
       "      <td>4.000</td>\n",
       "      <td>83.750</td>\n",
       "      <td>3.000</td>\n",
       "      <td>3.000</td>\n",
       "      <td>4.000</td>\n",
       "      <td>8379.000</td>\n",
       "      <td>20461.500</td>\n",
       "      <td>4.000</td>\n",
       "      <td>18.00</td>\n",
       "      <td>3.000</td>\n",
       "      <td>4.000</td>\n",
       "      <td>80.0</td>\n",
       "      <td>1.000</td>\n",
       "      <td>15.000</td>\n",
       "      <td>3.000</td>\n",
       "      <td>3.000</td>\n",
       "      <td>9.000</td>\n",
       "      <td>7.000</td>\n",
       "      <td>3.000</td>\n",
       "      <td>7.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>60.000</td>\n",
       "      <td>1499.000</td>\n",
       "      <td>29.000</td>\n",
       "      <td>5.000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2068.000</td>\n",
       "      <td>4.000</td>\n",
       "      <td>100.000</td>\n",
       "      <td>4.000</td>\n",
       "      <td>5.000</td>\n",
       "      <td>4.000</td>\n",
       "      <td>19999.000</td>\n",
       "      <td>26999.000</td>\n",
       "      <td>9.000</td>\n",
       "      <td>25.00</td>\n",
       "      <td>4.000</td>\n",
       "      <td>4.000</td>\n",
       "      <td>80.0</td>\n",
       "      <td>3.000</td>\n",
       "      <td>40.000</td>\n",
       "      <td>6.000</td>\n",
       "      <td>4.000</td>\n",
       "      <td>40.000</td>\n",
       "      <td>18.000</td>\n",
       "      <td>15.000</td>\n",
       "      <td>17.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Age  DailyRate  DistanceFromHome  Education  EmployeeCount  \\\n",
       "count  1470.000   1470.000          1470.000   1470.000         1470.0   \n",
       "mean     36.924    802.486             9.193      2.913            1.0   \n",
       "std       9.135    403.509             8.107      1.024            0.0   \n",
       "min      18.000    102.000             1.000      1.000            1.0   \n",
       "25%      30.000    465.000             2.000      2.000            1.0   \n",
       "50%      36.000    802.000             7.000      3.000            1.0   \n",
       "75%      43.000   1157.000            14.000      4.000            1.0   \n",
       "max      60.000   1499.000            29.000      5.000            1.0   \n",
       "\n",
       "       EmployeeNumber  EnvironmentSatisfaction  HourlyRate  JobInvolvement  \\\n",
       "count        1470.000                 1470.000    1470.000        1470.000   \n",
       "mean         1024.865                    2.722      65.891           2.730   \n",
       "std           602.024                    1.093      20.329           0.712   \n",
       "min             1.000                    1.000      30.000           1.000   \n",
       "25%           491.250                    2.000      48.000           2.000   \n",
       "50%          1020.500                    3.000      66.000           3.000   \n",
       "75%          1555.750                    4.000      83.750           3.000   \n",
       "max          2068.000                    4.000     100.000           4.000   \n",
       "\n",
       "       JobLevel  JobSatisfaction  MonthlyIncome  MonthlyRate  \\\n",
       "count  1470.000         1470.000       1470.000     1470.000   \n",
       "mean      2.064            2.729       6502.931    14313.103   \n",
       "std       1.107            1.103       4707.957     7117.786   \n",
       "min       1.000            1.000       1009.000     2094.000   \n",
       "25%       1.000            2.000       2911.000     8047.000   \n",
       "50%       2.000            3.000       4919.000    14235.500   \n",
       "75%       3.000            4.000       8379.000    20461.500   \n",
       "max       5.000            4.000      19999.000    26999.000   \n",
       "\n",
       "       NumCompaniesWorked  PercentSalaryHike  PerformanceRating  \\\n",
       "count            1470.000            1470.00           1470.000   \n",
       "mean                2.693              15.21              3.154   \n",
       "std                 2.498               3.66              0.361   \n",
       "min                 0.000              11.00              3.000   \n",
       "25%                 1.000              12.00              3.000   \n",
       "50%                 2.000              14.00              3.000   \n",
       "75%                 4.000              18.00              3.000   \n",
       "max                 9.000              25.00              4.000   \n",
       "\n",
       "       RelationshipSatisfaction  StandardHours  StockOptionLevel  \\\n",
       "count                  1470.000         1470.0          1470.000   \n",
       "mean                      2.712           80.0             0.794   \n",
       "std                       1.081            0.0             0.852   \n",
       "min                       1.000           80.0             0.000   \n",
       "25%                       2.000           80.0             0.000   \n",
       "50%                       3.000           80.0             1.000   \n",
       "75%                       4.000           80.0             1.000   \n",
       "max                       4.000           80.0             3.000   \n",
       "\n",
       "       TotalWorkingYears  TrainingTimesLastYear  WorkLifeBalance  \\\n",
       "count           1470.000               1470.000         1470.000   \n",
       "mean              11.280                  2.799            2.761   \n",
       "std                7.781                  1.289            0.706   \n",
       "min                0.000                  0.000            1.000   \n",
       "25%                6.000                  2.000            2.000   \n",
       "50%               10.000                  3.000            3.000   \n",
       "75%               15.000                  3.000            3.000   \n",
       "max               40.000                  6.000            4.000   \n",
       "\n",
       "       YearsAtCompany  YearsInCurrentRole  YearsSinceLastPromotion  \\\n",
       "count        1470.000            1470.000                 1470.000   \n",
       "mean            7.008               4.229                    2.188   \n",
       "std             6.127               3.623                    3.222   \n",
       "min             0.000               0.000                    0.000   \n",
       "25%             3.000               2.000                    0.000   \n",
       "50%             5.000               3.000                    1.000   \n",
       "75%             9.000               7.000                    3.000   \n",
       "max            40.000              18.000                   15.000   \n",
       "\n",
       "       YearsWithCurrManager  \n",
       "count              1470.000  \n",
       "mean                  4.123  \n",
       "std                   3.568  \n",
       "min                   0.000  \n",
       "25%                   2.000  \n",
       "50%                   3.000  \n",
       "75%                   7.000  \n",
       "max                  17.000  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " figure 01\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 2520x1800 with 35 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 查看所有数据分布\n",
    "colnm = df.columns.to_list()\n",
    "plt.figure(figsize=(35, 25))\n",
    "for i in range(35):\n",
    "    plt.subplot(5, 7, i+1)  # 3行4列 位置是i+1的子图\n",
    "    df[colnm[i]].hist(bins=80, color=colors[1])  # bins 指定显示多少竖条\n",
    "    plt.xlabel(colnm[i], fontsize=13)\n",
    "    plt.ylabel('Frequency')\n",
    "plt.tight_layout()\n",
    "print('\\n figure 01')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "得出结论： 该公司员工平均年龄为36岁  平均工作年限为11年，最长工作年限为40年 月平均收入为6502.93等重要信息"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " figure 02\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1080x648 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 公司各部门离职率分析\n",
    "plt.figure(figsize=(15, 9))  # 图片大小\n",
    "df1 = pd.crosstab(df['Department'], df['Attrition'])\n",
    "df1.plot(kind='bar')\n",
    "plt.legend()\n",
    "plt.xlabel('部门')\n",
    "plt.ylabel('人数')\n",
    "plt.xticks(rotation=0)\n",
    "plt.title('公司各部门离职率分析')\n",
    "print('\\n figure 02')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "得出结论：公司主要由三个部门组成（人力资源，科技部门，销售部门），其中科技部门的总人数最多，相对应的离职人数也是最多的，人力资源部门总人数和离职人数都最少"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " figure 03\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 公司离职人数占比分析\n",
    "labels = ['离职', '在职']\n",
    "sizes = [sum(df['Attrition'] == 'Yes'), sum(df['Attrition'] == 'No')]\n",
    "explode = (0, 0.001)\n",
    "plt.pie(sizes, explode=explode, labels=labels, autopct='%1.1f%%', shadow=False, startangle=150)\n",
    "plt.title(\"公司离职人数占比分析\")\n",
    "print('\\n figure 03')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "得出结论：公司离职率是16%"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " figure 04\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 加班与离职率的关系\n",
    "plt.figure(figsize=(6, 4))\n",
    "sns.countplot(x='OverTime', hue='Attrition', data=df, color=colors[4])\n",
    "plt.legend()\n",
    "plt.xlabel('加班时长')\n",
    "plt.title('加班与离职率的关系')\n",
    "print('\\n figure 04')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "得出结论：加班时间越长，员工的离职率越高，加班是导致离职的重要原因"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " figure 05\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 商务出差与离职率的关系\n",
    "plt.figure(figsize=(6, 4))\n",
    "sns.countplot(x='BusinessTravel', hue='Attrition', data=df)\n",
    "plt.legend()\n",
    "plt.xlabel('商务出差频次')\n",
    "plt.title('商务出差与离职率的关系')\n",
    "print('\\n figure 05')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "得出结论：如果频繁的商务出差，员工的离职率会更高"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " figure 06\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 教育程度与离职率的关系\n",
    "plt.figure(figsize=(6, 4))\n",
    "sns.countplot(x='Education', hue='Attrition', data=df, color=colors[6])\n",
    "plt.legend()\n",
    "plt.xlabel('教育程度')\n",
    "plt.title('教育程度与离职率的关系')\n",
    "print('\\n figure 06')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "得出结论：科技公司大部分学历中偏上，教育程度越高，更有竞争力，离职率也越低"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " figure 07\n"
     ]
    },
    {
     "data": {
      "image/png": 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sQw5/M7MMOfzNzDLk8Dczy5DD38wsQ50a/pJ6SnpR0oLi53BJsyU9Iml6yXo7tJmZWf10ds//COAnEdEaEa3ASKApIiYAIySNlDS5vK2TazAzs53o2cnbGw+cJOlY4DfARmBOsWw+MBEYU6Ht2fINSZoCTAEYOnRoJ5eZtzl3jGt0CbuNU095rNElmDVEZ/f8/w04LiLGAb2AE4EVxbLXgEFAvwptO4iIWRHREhEtzc3NnVymmVneOjv8n4iIPxTTi4F9gb7FfP/i+dZVaDMzszrq7OC9RdJoSU3Ap4GppGEdgNHAMmBJhTYzM6ujzh7z/1vgdkDAXOAuYKGkwaQhoPFAVGgzM7M66tTwj4jfks74eYukVuB4YGZErKnWZmZm9dPZPf8dRMRqtp3dU7XNzMzqxwdbzcwy5PA3M8uQw9/MLEMOfzOzDDn8zcwy5PA3M8uQw9/MLEMOfzOzDDn8zcwy5PA3M8uQw9/MLEMOfzOzDDn8zcwy5PA3M8uQw9/MLEMOfzOzDL2j8Jc0cedrmZnZ7qpD4S/pl2VNl9egFjMzq5N2v8ZR0hHAGOBASV8omvsBG2pdmJmZ1c7Oev6q8HsVcGq7D5IGSfr3Ynq2pEckTS9ZvkObmZnVT7s9/4h4HHhc0iERcfPb2O4PgL6SJgNNETFB0g2SRgKHl7dFxLPv/CWYmdnb1W74l7hS0ulA77aGajsDSR8B/gy8DLQCc4pF84GJpGGk8jaHv5lZHXX0bJ9fAH9BGvZp+9mBpN7Ad4BpRVM/YEUx/RowqEpbpW1NkbRY0uKVK1d2sEwzM+uIjvb8/xQRMzqw3jTgmoh4XRLAOqBvsaw/aWdTqW0HETELmAXQ0tISHazTzMw6oKPhv1DST4CbSUM6RMSDFdY7DviIpKnAB4ChwEvAImA0sBRYThrqKW0zM7M66mj4bwaeBj5IGvIJYIfwj4hj2qYlLQA+SdpxDAZOBMYXjy1vMzOzOupo+C8jhXZb8O9URLQCSGoFjgdmRsSaam1mZlY/HQ1/SMHfFzgBeJU0BLRTEbGabWf3VG0zM7P66VD4R8Q/lcz+o6RralSPmZnVQYfCX9IxJbP7Ae+vTTlmZlYPHR32OZZtY/2bgKm1KcfMzOqhoxd5XQb8EdiHNN7v0zPNzLqwjob/DaQrce8FDgRurFlFZmZWcx0d9jkoIj5fTM+T9ECtCjIzs9rraPj/XtIFwKPABLbdm8fMzLqgjg77nEPaUZwMrAX+umYVmZlZzXU0/G8FXoyIrwJ7ko4BmJlZF9XR8H9324VeEXEZsG/tSjIzs1rr6Jj/cknnA4+Rbu72Su1KMjOzWutoz/9M4A3SmP964Iu1KsjMzGqvo/f22Qj8qMa1mJlZnXS0529mZt2Iw9/MLEMOfzOzDDn8zcwy5PA3M8tQTcJf0j6Sjpfki8HMzHZDnR7+kt4N3AOMA+6X1CxptqRHJE0vWW+HNjMzq49a9PyPAL4ZEZcC84CPAE0RMQEYIWmkpMnlbTWow8zMqujo7R06LCIegLe+93cc6du/5hSL5wMTgTEV2p7t7FrMzKyyWo35CzgNWE367t+2+/+/RvpGsH4V2sq3MUXSYkmLV65cWYsyzcyyVZPwj2Qq8ARwFNC3WNS/eM51FdrKtzErIloioqW5ubkWZZqZZasWB3zPl/SFYnYAcAVpWAdgNLAMWFKhzczM6qTTx/yBWcAcSWcDvwXuAh6UNBg4ERhPGgpaWNZmZmZ1UosDvquB40vbJLUWbTMjYk21NjMzq49a9Px3UOwQ5uyszczM6sO3dzAzy5DD38wsQw5/M7MMOfzNzDLk8Dczy5DD38wsQw5/M7MMOfzNzDLk8Dczy5DD38wsQw5/M7MMOfzNzDLk8Dczy5DD38wsQw5/M7MMOfzNzDLk8Dczy5DD38wsQw5/M7MMOfzNzDLU6eEvaW9J90qaL+lOSb0lzZb0iKTpJevt0GZmZvVRi57/fwf+PiImAS8DpwNNETEBGCFppKTJ5W01qMPMzKro2dkbjIhrSmabgc8BVxbz84GJwBhgTlnbs6XbkTQFmAIwdOjQzi7TzCxrNRvzlzQBeDfwErCiaH4NGAT0q9C2nYiYFREtEdHS3NxcqzLNzLJUk/CXtA/wI+BLwDqgb7Gof/GcldrMzKxOanHAtzdwB3BBRLwALCEN6wCMBpZVaTMzszrp9DF/4MvAWOAiSRcBNwKflzQYOBEYDwSwsKzNzMzqpBYHfK8Fri1tkzQXOB6YGRFrirbW8jYzM6uPWvT8dxARq9l2dk/VNjMzqw8faDUzy5DD38wsQw5/M7MMOfzNzDLk8Dczy5DD38wsQw5/M7MM1eU8fzOr7vU1Lza6BMuQe/5mZhly+JuZZcjhb2aWIYe/mVmGHP5mZhly+JuZZcjhb2aWIYe/mVmGHP5mZhly+JuZZcjhb2aWoZqEv6RBkhaWzM+W9Iik6e21mZlZfXR6+Et6N/BPQL9ifjLQFBETgBGSRlZq6+w6zMysulr0/N8ETgPWFvOtwJxiej4wsUrbdiRNkbRY0uKVK1fWoEwzs3x1evhHxNqIWFPS1A9YUUy/Bgyq0la+nVkR0RIRLc3NzZ1dpplZ1upxwHcd0LeY7l88Z6U2MzOrk3qE7hK2DeuMBpZVaTMzszqpxzd53QUslDQYOBEYD0SFtprytyWZmW1Ts55/RLQWv9eSDvAuAo6NiDWV2mpVh5mZ7agu3+EbEavZdnZP1TYzM6sPH2g1M8uQw9/MLEMOfzOzDDn8zcwy5PA3M8uQw9/MLEMOfzOzDDn8zcwy5PA3M8uQw9/MLEMOfzOzDDn8zcwy5PA3M8uQw9/MLEMOfzOzDDn8zcwy5PA3M8uQw9/MLEMOfzOzDDU0/CXNlvSIpOmNrMPMLDcNC39Jk4GmiJgAjJA0slG1mJnlppE9/1ZgTjE9H5jYuFLMzPLSs4HP3Q9YUUy/BowtXShpCjClmF0naWkda+vu9gVebXQRu4PTUKNLsO35vVnopPfme6otaGT4rwP6FtP9KfsUEhGzgFn1LioHkhZHREuj6zAr5/dm/TRy2GcJ24Z6RgPLGleKmVleGtnzvwtYKGkwcCIwvoG1mJllpWE9/4hYSzrouwg4NiLWNKqWDHk4zXZXfm/WiSKi0TWYmVmd+QpfM7MMOfy7KEmXSHpK0oLi52udsM0FnVCaWUWSbpI0p5j+qaSb2ll3Qb3qylUjD/jarrs0Im5tdBFmb8Pokt+PNrKQ3Dn8uwlJewA3A/sBv4mIqZKWAK8Am4D9gRuBuaQrqwN4MCIuqrK9QcBNwN7A3RFxec1fhOVgk6SBwGagv6RfkC74fC4izqr0gErv7bpV24152Kdru6gY8rmGdDX0byPiGOAASUcAewCnAEcAfwUcCRwITCOdXvuJdrZ9AfB/I+Io4NPFP6zZrnocOK34vRH4EXAcMKzocFRS6b1tu8g9/67trWEfSdcCR0lqBQaQQv6PEbFO0gvAm4CALcDFpCus92xn24cAEySdSeqZDQZW1eh1WD5+DZwJ/IQ09HM2cBawD9uu+C93CDu+t5+odaHdnXv+3cdS4MqIaAWmAy9WWe+bwOWkf7r2zvNdCkwrtncF6f5LZrvq18AHi99NwD8DZwB/bucxHX1v29vg8O8+rgdOlPQgcA7wUpX17gH+kTT2/4akA6usdwXwLUkPAycAf+zkei1Py4BngBdIPfgLgH8tllV7L3b0vW1vgy/yMjPLkHv+ZmYZcvibmWXI4W9mliGHv1k7JDVJau+UWLMuyeFv1r7hFLcZljRY0l6S7pO0V9sKkh6Q9FDx87qkXiXLHpbk/zPb7fhNada+DZCCH/g66cKkDaRbZrTZEhETI2IisDgiNku6RdJ7gc0RsbXuVZvthK/wNatC0gTgk6QroWeSrkL9S9IOYK6kfsCxQJOk6cXDhklqIt26YNOOWzXbPbjnb1bdoaSL214FHgOaIuL4YvqTEXF0RGwCppJugLcB+BztXzlttltwz9+suk3AEuADpCuin5GktoWSegMHAx8H3ge03fyu2j1qzHYb7vmbVRERtwH/VUwvI90Wex4wjrQzuAtYTdpBBPAQ8Cfgo6Sb6GmHjZrtJhz+Zh0UETdFxCS2Dft8LCJeBhaQdgy3AU8C64HnSHdQNdstedjHrH0CVAz39IiIN99akE7h7AVcR/qCnJ7AYcDaiPgHSe8C+jegZrOdcvibte9dxc8RwA8ltfXm7yJ9cp4NLIuI70uaBBwFXFiyzn11rtesQ3xXTzOzDHnM38wsQw5/M7MMOfzNzDLk8Dczy5DD38wsQw5/M7MM/X+/8Ywli185mwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 性别与离职率的关系\n",
    "plt.figure(figsize=(6, 4))\n",
    "sns.countplot(x='Gender', hue='Attrition', data=df, color=colors[8])\n",
    "plt.legend()\n",
    "plt.xlabel('性别')\n",
    "plt.title('性别与离职率的关系')\n",
    "print('\\n figure 07')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "得出结论：科技公司男性人数比较多，通过公司人口基数来对比，女性的离职率是要高于男性的"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " figure 08\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 婚姻状况与离职率的关系\n",
    "labels = ['单身', '已婚', '离婚']\n",
    "sizes = [sum(df['MaritalStatus'] == 'Married'), sum(df['MaritalStatus'] == 'Single'), sum(df['MaritalStatus'] == 'Divorced')]\n",
    "explode = (0.04, 0, 0.001)\n",
    "plt.pie(sizes, explode=explode, labels=labels, autopct='%1.1f%%', shadow=False, startangle=150)\n",
    "plt.title(\"婚姻状况与离职率的关系\")\n",
    "print('\\n figure 08')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "得出结论：公司单身离职率最高，离婚后的离职率最低"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " figure 09\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 收入与离职率的关系\n",
    "df_income1 = df[(df['MonthlyIncome'] > 1000) & (df['MonthlyIncome'] < 8000)]\n",
    "df_income2 = df[(df['MonthlyIncome'] > 8000) & (df['MonthlyIncome'] < 15000)]\n",
    "df_income3 = df[(df['MonthlyIncome'] > 15000) & (df['MonthlyIncome'] < 20000)]\n",
    "labels = ['月收入小于8000离职率', '月收入8000-15000离职率', '月收入大于15000离职率']\n",
    "sizes = [sum(df_income1['Attrition'] == 'Yes'), sum(df['Attrition'] == 'Yes'),\n",
    "         sum(df['Attrition'] == 'Yes')]\n",
    "explode = (0.04, 0, 0.001)\n",
    "plt.pie(sizes, explode=explode, labels=labels, autopct='%1.1f%%', shadow=False, startangle=150)\n",
    "plt.title(\"收入与离职率的关系\")\n",
    "print('\\n figure 09')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "得出结论：公司单身离职率最高，离婚后的离职率最低"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " figure 10\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 员工工作过的公司与离职率的关系\n",
    "df_worked1 = df[(df['NumCompaniesWorked'] > 0) & (df['NumCompaniesWorked'] < 3)]\n",
    "df_worked2 = df[(df['NumCompaniesWorked'] > 3) & (df['NumCompaniesWorked'] < 6)]\n",
    "df_worked3 = df[(df['NumCompaniesWorked'] > 6) & (df['NumCompaniesWorked'] < 10)]\n",
    "x = ['0-3家', '3-6家', '6-10家']\n",
    "y = [sum(df_worked1['Attrition'] == 'Yes'), sum(df_worked2['Attrition'] == 'Yes'), sum(df_worked3['Attrition'] == 'Yes')]\n",
    "plt.plot(x, y, color='r')\n",
    "plt.xlabel('员工工作过公司数量')\n",
    "plt.ylabel('离职人数')\n",
    "plt.title(\"员工工作过的公司与离职率的关系\")\n",
    "print('\\n figure 10')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "得出结论：员工工作过的公司越少，离职率越低，说明频繁跳槽的员工稳定性较差，更容易离职。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "总结：\n",
    "\n",
    "1.加班是导致离职最重要的原因。\n",
    "建议：完善加班制度，可以对员工每月加班的时间进行限制。\n",
    "加强员工培训，合理安排工作时间的工作和会议安排，提高工作时间的工作效率。\n",
    "\n",
    "2.差旅次数过多也会导致员工离职。因为员工长期出差没办法兼顾家庭并且工作负担也比较大。\n",
    "建议：合理安排员工的差旅次数。例如实施轮流差旅措施\n",
    "\n",
    "3.工作年数也和离职率密切相关。工作年数越长，职位水平越高，离职率越低。\n",
    "建议：公司招聘时考察员工的稳定性，一般情况下，以前待过的公司越少越好。\n",
    "\n",
    "4.单身的人离职率较高。\n",
    "建议：公司多关照单身的人，别让加班耽误了单身青年谈恋爱，相亲的时间。"
   ]
  }
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